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Previously, we described the essentials of R programming and provided quick start guides for importing data into **R**.

Here, we’ll describe how to create **strip charts** (i.e., one dimensional scatter plots or dot plots) in R. These plots are a good alternative to box plots when sample sizes are small.

**Launch RStudio**as described here: Running RStudio and setting up your working directory**Prepare your data**as described here: Best practices for preparing your data and save it in an external .txt tab or .csv files**Import your data**into**R**as described here: Fast reading of data from txt|csv files into R: readr package.

Here, we’ll use the R built-in ToothGrowth data set.

`ToothGrowth$dose <- as.factor(ToothGrowth$dose)# Print the first 6 rowshead(ToothGrowth, 6)`

`## len supp dose## 1 4.2 VC 0.5## 2 11.5 VC 0.5## 3 7.3 VC 0.5## 4 5.8 VC 0.5## 5 6.4 VC 0.5## 6 10.0 VC 0.5`

`stripchart(x, data = NULL method = "overplot", jitter = 0.1)`

**x**: the data from which the plots are to be produced. Allowed values are one or a list of numeric vector, each corresponding to a component plot.**data**: a data.frame (or list) from which the variables in x should be taken.**Method**: the method to be used to separate coincident points. Allowed values are one of “overplot”, “jitter” or “stack”.**jitter**: when method = “jitter” is used, jitter gives the amount of jittering applied.

`# Plot len by dosestripchart(len ~ dose, data = ToothGrowth, pch = 19, frame = FALSE)`

`# Vertical plot using method = "jitter"stripchart(len ~ dose, data = ToothGrowth, pch = 19, frame = FALSE, vertical = TRUE, method = "jitter")`

`# Change point shapes (pch) and colors by groups# add main title and axis labelsstripchart(len ~ dose, data = ToothGrowth, frame = FALSE, vertical = TRUE, method = "jitter", pch = c(21, 18, 16), col = c("#999999", "#E69F00", "#56B4E9"), main = "Length by dose", xlab = "Dose", ylab = "Length")`

- Creating and Saving Graphs in R
- Scatter Plots
- Scatter Plot Matrices
- Box Plots
- Bar Plots
- Line Plots
- Pie Charts
- Histogram and Density Plots
- Dot Charts
- Plot Group Means and Confidence Intervals
- Graphical Parameters

- Lattice Graphs
- ggplot2 Graphs

This analysis has been performed using **R statistical software** (ver. 3.2.4).

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